CN110796099A - Vehicle overrun detection method and device - Google Patents
Vehicle overrun detection method and device Download PDFInfo
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- CN110796099A CN110796099A CN201911054049.4A CN201911054049A CN110796099A CN 110796099 A CN110796099 A CN 110796099A CN 201911054049 A CN201911054049 A CN 201911054049A CN 110796099 A CN110796099 A CN 110796099A
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- 238000001514 detection method Methods 0.000 title claims abstract description 65
- 238000012545 processing Methods 0.000 claims description 22
- 230000011218 segmentation Effects 0.000 claims description 10
- 238000005303 weighing Methods 0.000 claims description 9
- 230000000877 morphologic effect Effects 0.000 claims description 6
- 238000004806 packaging method and process Methods 0.000 claims description 3
- 230000006399 behavior Effects 0.000 abstract description 6
- 238000000034 method Methods 0.000 description 10
- 238000010586 diagram Methods 0.000 description 2
- 239000010453 quartz Substances 0.000 description 2
- VYPSYNLAJGMNEJ-UHFFFAOYSA-N silicon dioxide Inorganic materials O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 description 2
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 230000003628 erosive effect Effects 0.000 description 1
- 238000002372 labelling Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000012827 research and development Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/20—Image enhancement or restoration by the use of local operators
- G06T5/30—Erosion or dilatation, e.g. thinning
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/40—Image enhancement or restoration by the use of histogram techniques
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/50—Extraction of image or video features by performing operations within image blocks; by using histograms, e.g. histogram of oriented gradients [HoG]; by summing image-intensity values; Projection analysis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
- G08G1/0175—Detecting movement of traffic to be counted or controlled identifying vehicles by photographing vehicles, e.g. when violating traffic rules
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/60—Type of objects
- G06V20/62—Text, e.g. of license plates, overlay texts or captions on TV images
- G06V20/625—License plates
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V2201/00—Indexing scheme relating to image or video recognition or understanding
- G06V2201/08—Detecting or categorising vehicles
Abstract
The invention discloses a vehicle overrun detection method and a vehicle overrun detection device, wherein the vehicle type and the license plate of a vehicle are identified through shot vehicle images, the rated weight and the rated number of people of the vehicle are determined, the actual number of people is determined by utilizing the infrared images of the vehicle, the vehicle overrun is further judged, and the judgment result is uploaded to an upper computer, so that two illegal overrun behaviors are simultaneously detected.
Description
Technical Field
The embodiment of the invention relates to the technical field of vehicle detection, in particular to a vehicle overrun detection method and device.
Background
Nowadays, the urbanization phenomenon is increasingly serious, and the intelligent traffic is rapidly developed. The target recognition is an important component of computer vision, drives the development of a vehicle detection and recognition system, and has important practical significance.
With the improvement of the informatization level of intelligent traffic management, the off-site law enforcement system becomes a hot spot for research and development at home and abroad. The off-site law enforcement system mainly needs to realize that according to the recorded data of the technical monitoring equipment, the party of the illegal and over-limited transport vehicle is penalized legally. The illegal overrun includes the limit of the number of people in real load and the load limit.
In some special periods, for example, during holidays, besides the load detection of the trucks, the real-load number of passenger vehicles such as passenger cars also needs to be detected in real time, so as to avoid the behavior of private reception of passengers during the running of the passenger cars.
Disclosure of Invention
The embodiment of the invention provides a vehicle overrun detection method and device, which can be used for simultaneously detecting two illegal overrun behaviors.
In view of the above, a first aspect of the present invention provides a vehicle overrun detection method, including:
acquiring the actual weight of the vehicle detected by a weighing system;
acquiring a photographed vehicle image of the vehicle;
acquiring a shot infrared image of the vehicle;
determining the type, the license plate, the rated weight and the rated number of people of the vehicle according to the vehicle image;
determining the actual number of people contained in the vehicle according to the infrared image of the vehicle;
and if the actual weight of the vehicle is higher than the rated weight or the actual number of people contained in the vehicle exceeds the rated number of people, judging that the vehicle is out of limit, and packaging the out-of-limit information of the vehicle and the license plate of the vehicle and then uploading the information to an upper computer.
Optionally, the determining, according to the infrared image of the vehicle, the actual number of people included in the vehicle specifically includes:
performing ROI segmentation on the acquired infrared image of the vehicle, and determining a human body target region in the infrared image of the vehicle;
and carrying out target detection on the human body target area by utilizing a two-dimensional histogram template, and determining the number of human bodies included in the infrared image of the vehicle.
Optionally, the performing ROI segmentation on the acquired infrared image of the vehicle, and determining the human target region in the infrared image of the vehicle specifically includes:
carrying out highlight pixel detection on the infrared image of the vehicle to obtain a gray level histogram of the infrared image;
after morphological processing is carried out on the gray level histogram, a connected region in the gray level histogram is marked;
and combining the connected regions in the gray level histogram to determine a human body target region in the infrared image of the vehicle.
Optionally, the performing, by using a two-dimensional histogram template, target detection on the human target region, and determining the number of human bodies included in the infrared image of the vehicle specifically includes:
carrying out target detection on the human body target area by using a sample gray level histogram template, and marking the area with the difference value with the sample gray level histogram template higher than a first preset threshold value as the number of one human body;
and counting the number of the human bodies in the human body target area to obtain the number of the human bodies in the infrared image of the vehicle.
Optionally, the performing target detection on the human body target region by using the sample gray level histogram template, after marking a region whose difference value with the sample gray level histogram template is higher than a first preset threshold as the number of one human body, further includes:
carrying out target detection on the human body target area by utilizing a sample projection histogram, and marking the area with the difference value with the sample projection histogram template higher than a second preset threshold as the number of one human body;
correspondingly, the counting of the number of the human bodies included in the human body target area to obtain the number of the human bodies included in the infrared image of the vehicle is as follows:
and counting the number of the human bodies in the human body target area, which are simultaneously higher than the first preset threshold and the second preset threshold, so as to obtain the number of the human bodies in the infrared image of the vehicle.
A second aspect of the present invention provides a vehicle overrun detection apparatus, the apparatus comprising:
a first acquiring unit for acquiring the actual weight of the vehicle detected by the weighing system;
a second acquisition unit configured to acquire a vehicle image of the vehicle photographed;
a third acquisition unit configured to acquire a photographed infrared image of the vehicle;
the first determining unit is used for determining the type, the license plate, the rated weight and the rated number of people of the vehicle according to the vehicle image;
a second determination unit for determining the actual number of persons contained in the vehicle from the infrared image of the vehicle;
and the detection unit is used for judging that the vehicle is out of limit if the actual weight of the vehicle is higher than the rated weight or the actual number of people contained in the vehicle exceeds the rated number of people, and uploading the out-of-limit information of the vehicle and the license plate of the vehicle to an upper computer after being packaged.
Optionally, the second determining unit specifically includes:
the first processing subunit is used for performing ROI segmentation on the acquired infrared image of the vehicle and determining a human body target region in the infrared image of the vehicle;
and the second processing subunit is used for performing target detection on the human body target area by using a two-dimensional histogram template and determining the number of human bodies included in the infrared image of the vehicle.
Optionally, the first processing subunit is specifically configured to:
carrying out highlight pixel detection on the infrared image of the vehicle to obtain a gray level histogram of the infrared image;
after morphological processing is carried out on the gray level histogram, a connected region in the gray level histogram is marked;
and combining the connected regions in the gray level histogram to determine a human body target region in the infrared image of the vehicle.
Optionally, the second processing subunit is specifically configured to:
carrying out target detection on the human body target area by using a sample gray level histogram template, and marking the area with the difference value with the sample gray level histogram template higher than a first preset threshold value as the number of one human body;
and counting the number of the human bodies in the human body target area to obtain the number of the human bodies in the infrared image of the vehicle.
Optionally, the second processing subunit is further configured to:
carrying out target detection on the human body target area by utilizing a sample projection histogram, and marking the area with the difference value with the sample projection histogram template higher than a second preset threshold as the number of one human body;
correspondingly, the counting of the number of the human bodies included in the human body target area to obtain the number of the human bodies included in the infrared image of the vehicle is as follows:
and counting the number of the human bodies in the human body target area, which are simultaneously higher than the first preset threshold and the second preset threshold, so as to obtain the number of the human bodies in the infrared image of the vehicle.
According to the technical scheme, the embodiment of the invention has the following advantages:
the embodiment of the invention provides a vehicle overrun detection method, which is characterized in that the vehicle type and the license plate of a vehicle are identified through shot vehicle images, the rated weight and the rated number of people of the vehicle are determined, the actual number of people is determined by utilizing the infrared images of the vehicle, the vehicle overrun is further judged, and the judgment result is uploaded to an upper computer, so that two illegal overrun behaviors are detected at the same time.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
FIG. 1 is a flow chart of a method for vehicle over-limit detection in an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a vehicle overrun detection device in an embodiment of the invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention designs a vehicle overrun detection method and a vehicle overrun detection device, which can simultaneously detect two illegal overrun behaviors.
For convenience of understanding, please refer to fig. 1, in which fig. 1 is a flowchart illustrating a method for detecting vehicle over-limit according to an embodiment of the present invention, as shown in fig. 1, specifically:
101. acquiring the actual weight of the vehicle detected by a weighing system;
it should be noted that the weighing system is generally a quartz weighing sensor, and the actual weight of the moving vehicle is obtained by the quartz weighing sensor, so as to implement non-stop detection.
102. Acquiring a photographed vehicle image of the vehicle;
the high-definition cameras disposed above or on both sides of the road capture vehicle images of the vehicle, typically, front images of the vehicle.
103. Acquiring a shot infrared image of the vehicle;
the infrared image of the vehicle, which is typically a front view image or a plan view image of the vehicle, is captured by an infrared camera or a camera installed above the road.
104. Determining the type, the license plate, the rated weight and the rated number of people of the vehicle according to the vehicle image;
it should be noted that the vehicle type and the license plate of the vehicle are identified by a general vehicle type identification algorithm and a license plate identification algorithm, and the rated weight and the rated number of people of the vehicle are determined according to the identified vehicle type.
105. Determining the actual number of people contained in the vehicle according to the infrared image of the vehicle;
specifically, the method includes:
performing ROI segmentation on the acquired infrared image of the vehicle, and determining a human body target region in the infrared image of the vehicle, specifically:
carrying out highlight pixel detection on the infrared image of the vehicle to obtain a gray level histogram of the infrared image;
it should be noted that the ROI segmentation is to segment a potential target region in the infrared image, so as to facilitate subsequent target detection operations, and the first step is highlight pixel detection. Generally, the infrared image is insensitive to light and is only sensitive to heat, and the ambient temperature of a scene is relatively uniform, so that compared with a visible light image, the gray distribution rule of the infrared image is relatively obvious, the gray distribution of the infrared image is described through a gray histogram, and whether a certain pixel in the gray histogram belongs to a high-brightness pixel is detected, so that the binarization process of the infrared image is completed.
After morphological processing is carried out on the gray level histogram, a connected region in the gray level histogram is marked;
it should be noted that the gray histogram also contains much background noise, mainly some pixels or small regions with high brightness, so that the result of the highlight region detection can be processed by morphology, and then the operation of erosion and then expansion, that is, the on operation, is performed. The highlight pixel detection result contains many separated connected regions, and in order to perform the following operation, the regions must be marked, that is, the circumscribed rectangular coordinates of the regions are acquired.
Merging the connected regions in the gray level histogram to determine a human body target region in the infrared image of the vehicle;
it should be noted that, due to the fact that incomplete target connected regions may occur in the labeling result, or a single target is labeled as multiple connected regions, an error occurs in the subsequent target recognition operation, and in order to solve the problem, connected regions in the gray histogram need to be merged.
Carrying out target detection on the human body target area by utilizing a two-dimensional histogram template, and determining the number of human bodies included in the infrared image of the vehicle, wherein the method specifically comprises the following steps:
carrying out target detection on the human body target area by using a sample gray level histogram template, and marking the area with the difference value with the sample gray level histogram template higher than a first preset threshold value as the number of one human body;
carrying out target detection on the human body target area by utilizing a sample projection histogram, and marking the area with the difference value with the sample projection histogram template higher than a second preset threshold as the number of one human body;
and counting the number of the human bodies in the human body target area, which are simultaneously higher than the first preset threshold and the second preset threshold, so as to obtain the number of the human bodies in the infrared image of the vehicle.
It should be noted that, after ROI segmentation is completed, object detection is performed next, and shape matching is the most direct method, but because the posture of a human body varies greatly, the shape matching method needs to establish more shape templates, and how to extract the complete contour of an object needs to be considered, so that object matching can be performed through a two-dimensional histogram template, specifically, a sample grayscale histogram template and a sample projection histogram template, and it is necessary to match two sample templates at the same time to determine the number of a human body in a human body object region.
106. If the actual weight of the vehicle is higher than the rated weight or the actual number of people in the vehicle exceeds the rated number of people, judging that the vehicle is out of limit, packaging the out-of-limit information of the vehicle and the license plate of the vehicle, and uploading the information to an upper computer;
it should be noted that if the actual weight of the detected vehicle is higher than the rated weight of the vehicle type, or the actual number of people included in the detected vehicle exceeds the rated number of people of the vehicle type, the vehicle can be judged to be out of limit, and the out-of-limit information, namely the load out-of-limit or the number of people out-of-limit or both out-of-limit and the license plate of the vehicle are packaged and then uploaded to the upper computer for recording and subsequent processing.
The embodiment of the invention provides a vehicle overrun detection method, which is characterized in that the vehicle type and the license plate of a vehicle are identified through shot vehicle images, the rated weight and the rated number of people of the vehicle are determined, the actual number of people is determined by utilizing the infrared images of the vehicle, the vehicle overrun is further judged, and the judgment result is uploaded to an upper computer, so that two illegal overrun behaviors are detected at the same time.
Referring to fig. 2, fig. 2 is a schematic structural diagram of a vehicle overrun detection device provided in the present invention, as shown in fig. 2, specifically including:
a first acquiring unit 201 for acquiring an actual weight of the vehicle detected by the weighing system;
a second acquisition unit 202 for acquiring a captured vehicle image of the vehicle;
a third acquisition unit 203 for acquiring a photographed infrared image of the vehicle;
a first determining unit 204, configured to determine a vehicle type, a license plate, a rated weight thereof, and a rated number of people of the vehicle according to the vehicle image;
a second determination unit 205 for determining the actual number of persons included in the vehicle from the infrared image of the vehicle;
and the detection unit 206 is used for judging that the vehicle is out of limit if the actual weight of the vehicle is higher than the rated weight or the actual number of people contained in the vehicle exceeds the rated number of people, and uploading the out-of-limit information of the vehicle and the license plate of the vehicle to an upper computer after being packaged.
Further, the second determining unit 205 specifically includes:
the first processing subunit is used for performing ROI segmentation on the acquired infrared image of the vehicle and determining a human body target region in the infrared image of the vehicle;
and the second processing subunit is used for performing target detection on the human body target area by using a two-dimensional histogram template and determining the number of human bodies included in the infrared image of the vehicle.
Further, the first processing subunit is specifically configured to:
carrying out highlight pixel detection on the infrared image of the vehicle to obtain a gray level histogram of the infrared image;
after morphological processing is carried out on the gray level histogram, a connected region in the gray level histogram is marked;
and combining the connected regions in the gray level histogram to determine a human body target region in the infrared image of the vehicle.
Further, the second processing subunit is specifically configured to:
carrying out target detection on the human body target area by using a sample gray level histogram template, and marking the area with the difference value with the sample gray level histogram template higher than a first preset threshold value as the number of one human body;
and counting the number of the human bodies in the human body target area to obtain the number of the human bodies in the infrared image of the vehicle.
Further, the second processing subunit is further configured to:
carrying out target detection on the human body target area by utilizing a sample projection histogram, and marking the area with the difference value with the sample projection histogram template higher than a second preset threshold as the number of one human body;
correspondingly, the counting of the number of the human bodies included in the human body target area to obtain the number of the human bodies included in the infrared image of the vehicle is as follows:
and counting the number of the human bodies in the human body target area, which are simultaneously higher than the first preset threshold and the second preset threshold, so as to obtain the number of the human bodies in the infrared image of the vehicle.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
Claims (10)
1. A vehicle overrun detection method, comprising:
acquiring the actual weight of the vehicle detected by a weighing system;
acquiring a photographed vehicle image of the vehicle;
acquiring a shot infrared image of the vehicle;
determining the type, the license plate, the rated weight and the rated number of people of the vehicle according to the vehicle image;
determining the actual number of people contained in the vehicle according to the infrared image of the vehicle;
and if the actual weight of the vehicle is higher than the rated weight or the actual number of people contained in the vehicle exceeds the rated number of people, judging that the vehicle is out of limit, and packaging the out-of-limit information of the vehicle and the license plate of the vehicle and then uploading the information to an upper computer.
2. The vehicle over-limit detection method according to claim 1, wherein the determining the actual number of people included in the vehicle from the infrared image of the vehicle specifically comprises:
performing ROI segmentation on the acquired infrared image of the vehicle, and determining a human body target region in the infrared image of the vehicle;
and carrying out target detection on the human body target area by utilizing a two-dimensional histogram template, and determining the number of human bodies included in the infrared image of the vehicle.
3. The vehicle over-limit detection method according to claim 2, wherein the performing ROI segmentation on the acquired infrared image of the vehicle and determining the human target region in the infrared image of the vehicle specifically comprises:
carrying out highlight pixel detection on the infrared image of the vehicle to obtain a gray level histogram of the infrared image;
after morphological processing is carried out on the gray level histogram, a connected region in the gray level histogram is marked;
and combining the connected regions in the gray level histogram to determine a human body target region in the infrared image of the vehicle.
4. The vehicle overrun detection method according to claim 2, wherein the performing of the target detection on the human target area by using the two-dimensional histogram template, and the determining of the number of human bodies included in the infrared image of the vehicle specifically includes:
carrying out target detection on the human body target area by using a sample gray level histogram template, and marking the area with the difference value with the sample gray level histogram template higher than a first preset threshold value as the number of one human body;
and counting the number of the human bodies in the human body target area to obtain the number of the human bodies in the infrared image of the vehicle.
5. The vehicle over-limit detection method according to claim 4, wherein the performing target detection on the human target region by using a sample gray histogram template, after marking a region having a difference value higher than a first preset threshold value from the sample gray histogram template as the number of one human body, further comprises:
carrying out target detection on the human body target area by utilizing a sample projection histogram, and marking the area with the difference value with the sample projection histogram template higher than a second preset threshold as the number of one human body;
correspondingly, the counting of the number of the human bodies included in the human body target area to obtain the number of the human bodies included in the infrared image of the vehicle is as follows:
and counting the number of the human bodies in the human body target area, which are simultaneously higher than the first preset threshold and the second preset threshold, so as to obtain the number of the human bodies in the infrared image of the vehicle.
6. A vehicle overrun detection device, comprising:
a first acquiring unit for acquiring the actual weight of the vehicle detected by the weighing system;
a second acquisition unit configured to acquire a vehicle image of the vehicle photographed;
a third acquisition unit configured to acquire a photographed infrared image of the vehicle;
the first determining unit is used for determining the type, the license plate, the rated weight and the rated number of people of the vehicle according to the vehicle image;
a second determination unit for determining the actual number of persons contained in the vehicle from the infrared image of the vehicle;
and the detection unit is used for judging that the vehicle is out of limit if the actual weight of the vehicle is higher than the rated weight or the actual number of people contained in the vehicle exceeds the rated number of people, and uploading the out-of-limit information of the vehicle and the license plate of the vehicle to an upper computer after being packaged.
7. The vehicle overrun detection device as recited in claim 6, wherein the second determination unit specifically includes:
the first processing subunit is used for performing ROI segmentation on the acquired infrared image of the vehicle and determining a human body target region in the infrared image of the vehicle;
and the second processing subunit is used for performing target detection on the human body target area by using a two-dimensional histogram template and determining the number of human bodies included in the infrared image of the vehicle.
8. The vehicle over-limit detection device according to claim 7, wherein the first processing subunit is specifically configured to:
carrying out highlight pixel detection on the infrared image of the vehicle to obtain a gray level histogram of the infrared image;
after morphological processing is carried out on the gray level histogram, a connected region in the gray level histogram is marked;
and combining the connected regions in the gray level histogram to determine a human body target region in the infrared image of the vehicle.
9. The vehicle over-limit detection device according to claim 7, wherein the second processing subunit is specifically configured to:
carrying out target detection on the human body target area by using a sample gray level histogram template, and marking the area with the difference value with the sample gray level histogram template higher than a first preset threshold value as the number of one human body;
and counting the number of the human bodies in the human body target area to obtain the number of the human bodies in the infrared image of the vehicle.
10. The vehicle over-limit detection device of claim 8, wherein the second processing subunit is further configured to:
carrying out target detection on the human body target area by utilizing a sample projection histogram, and marking the area with the difference value with the sample projection histogram template higher than a second preset threshold as the number of one human body;
correspondingly, the counting of the number of the human bodies included in the human body target area to obtain the number of the human bodies included in the infrared image of the vehicle is as follows:
and counting the number of the human bodies in the human body target area, which are simultaneously higher than the first preset threshold and the second preset threshold, so as to obtain the number of the human bodies in the infrared image of the vehicle.
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| CN114419329A (en) * | 2022-03-30 | 2022-04-29 | 浙江大华技术股份有限公司 | Vehicle manned number detection method and device |
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